Climate Sensitivity, Sc, estimated for 5 deg X 5 deg rectangles of the earth’s surface. Each estimate is derived from the time series of annual average surface air temperature of the rectangle using the ARX method with the time series of ln(CO2 concentration) as the exogenous variable. Only those estimates from rectangles with more than 50 data points and unselfcorrelated residuals are shown. Displayed values have been rounded to the nearest integer.

We use a statistical method to estimate both global and regional climate sensitivity from observed time series while making no assumptions about the underlying physics.


A theoretical misconception is the idea that fluids can be adequately described as a “continuum”, an infinitely divisible substance, an idea that evolved from the mediaeval concept of a plenum, a space completely filled with matter. “Continuum” works well enough for streamline flows but breaks down mathematically for flows that exceed the critical Reynold’s number. It is a deterministic description that cannot accommodate the stochastic phenomena of entropy and turbulence. The plenum has been abandoned by every branch of physics other than fluid dynamics. Numerical circulation models continue to depend heavily on the continuum concept and on the deterministic equations that support it. Sadly, real-world fluid flows are dominated by turbulence but this is ignored or trivialised in circulation models. Turbulence is even evident in experiments as a Quantum Mechanical phenomenon.

Climate science is, or should be, a branch of experimental physics depending on observation rather than theoretical preconceptions. It is primarily concerned with the relationships between time series of measurable physical quantities and their long term behaviour. Here we develop a rigorous and useful statistical calculus of time series and apply it to real world data. We look at how both global and regional surface air temperature time series are related to atmospheric carbon dioxide concentration. We reveal geographic patterns of climate sensitivity which, to date, have eluded climate modellers.

The full paper can be downloaded here: ReidNielsen

Journal Decision

Board Member
Comments to Author(s):
This paper uses a statistical method to estimate climate sensitivity. This paper is not suitable for Proceedings A as it does not meet several criteria – it does not provide strong evidence for its conclusions, the results are not novel, and the conclusions of the paper are not significant.